priyadarshi kanungo and pradipta kumar nanda pga based thresholding schemes for image segmentation

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Siddhartha Bhattacharyya Hybrid Intelligence for Image Analysis and Understanding

A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Divided into self-contained chapters. Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms. Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms. The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.

10194.65 рублей

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Tsiptsis Konstantinos K. Data Mining Techniques in CRM. Inside Customer Segmentation

This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.

7485.81 рублей

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Malcolm McDonald Market Segmentation. How to Do It and How to Profit from It

Market Segmentation: How to do it and how to profit from it, revised and updated 4th Edition is the only book that spells out a totally dispassionate, systematic process for arriving at genuine, needs-based segments that can enable organizations to escape from the dreay, miserable, downward pricing spiral which results from getting market segmentation wrong. Nothing in business works unless markets are correctly defined, mapped, quantified and segmented. Why else have hundreds of billions of dollars been wasted on excellent initiatives such as TQM, BPR, Balanced Scorecards, Six Sigma, Knolwedge Management, Innovation, Relationship Marketing and, latterly, CRM? The answer, of course, is because of a structured approach to market segmentation. Market Segmentation: How to do it and how to profit from it, revised and updated 4th Edition provides a structured, no-nonsense approach to getting market segmentation right. It is an essential text for professionals and students based on a wealth of practical experience and packed with examples and easily used checklists.

4967.61 рублей

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Oge Marques Practical Image and Video Processing Using MATLAB

Up-to-date, technically accurate coverage of essential topics in image and video processing This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation. The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation. Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®. Extra features of this book include: More than 30 MATLAB® tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB® Chapters supported by figures, examples, illustrative problems, and exercises Useful websites and an extensive list of bibliographical references This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own. Supplemental resources for readers and instructors can be found at http://www.ogemarques.com

13064.81 рублей

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J. Parker R. Algorithms for Image Processing and Computer Vision

A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.

7260.35 рублей

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Mark Haidekker Advanced Biomedical Image Analysis

A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. The accompanying live DVD contains a selection of image analysis software, and it provides most of the algorithms from the book so readers can immediately put their new knowledge to use. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.

12915.78 рублей

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Mark Haidekker Advanced Biomedical Image Analysis

A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. The accompanying live DVD contains a selection of image analysis software, and it provides most of the algorithms from the book so readers can immediately put their new knowledge to use. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.

12306.68 рублей

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Mohsen Pourahmadi High-Dimensional Covariance Estimation. With High-Dimensional Data

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.

6987.58 рублей

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Christine Fernandez-Maloigne Digital Color Imaging

This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images. For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image processing. It covers a wide range of topics related to computational color imaging, including color filtering and segmentation, color texture characterization, color invariant for object recognition, color and motion analysis, as well as color image and video indexing and retrieval. Contents 1. Color Representation and Processing in Polar Color Spaces, Jesús Angulo, Sébastien Lefèvre and Olivier Lezoray. 2. Adaptive Median Color Filtering, Frédérique Robert-Inacio and Eric Dinet. 3. Anisotropic Diffusion PDEs for Regularization of Multichannel Images: Formalisms and Applications, David Tschumperlé. 4. Linear Prediction in Spaces with Separate Achromatic and Chromatic Information,Olivier Alata, Imtnan Qazi, Jean-Christophe Burie and Christine Fernandez-Maloigne. 5. Region Segmentation, Alain Clément, Laurent Busin, Olivier Lezoray and Ludovic Macaire. 6. Color Texture Attributes, Nicolas Vandenbroucke, Olivier Alata, Christèle Lecomte, Alice Porebski and Imtnan Qazi. 7. Photometric Color Invariants for Object Recognition, Damien Muselet. 8. Color Key Point Detectors and Local Color Descriptors, Damien Muselet and Xiaohu Song. 9. Motion Estimation in Color Image Sequences, Bertrand Augereau and Jenny Benois-Pineau.

11647.58 рублей

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Xavier Descombes Stochastic Geometry for Image Analysis

This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

12610.09 рублей

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Antoni Llobet Molecular Water Oxidation Catalysis. A Key Topic for New Sustainable Energy Conversion Schemes

Photocatalytic water splitting is a promising strategy for capturing energy from the sun by coupling light harvesting and the oxidation of water, in order to create clean hydrogen fuel. Thus a deep knowledge of the water oxidation catalysis field is essential to be able to come up with useful energy conversion devices based on sunlight and water splitting. Molecular Water Oxidation Catalysis: A Key Topic for New Sustainable Energy Conversion Schemes presents a comprehensive and state-of-the-art overview of water oxidation catalysis in homogeneous phase, describing in detail the most important catalysts discovered today based on first and second row transition metals. A strong emphasis is placed on the description of their performance, as well as how they work from a mechanistic perspective. In addition, a theoretical description of some of the most relevant catalysts based on DFT are presented, as well as a description of related natural systems, such as the oxygen evolving system of photosystem II and the heme chlorite-dismutase. This book is a valuable resource for researchers working on water oxidation catalysis, solar energy conversion and artificial photosynthesis, as well as for chemists and materials scientists with a broad interest in new sustainable energy conversion schemes.

11286.94 рублей

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Jan Flusser 2D and 3D Image Analysis by Moments

Presents recent significant and rapid development in the field of 2D and 3D image analysis 2D and 3D Image Analysis by Moments, is a unique compendium of moment-based image analysis which includes traditional methods and also reflects the latest development of the field. The book presents a survey of 2D and 3D moment invariants with respect to similarity and affine spatial transformations and to image blurring and smoothing by various filters. The book comprehensively describes the mathematical background and theorems about the invariants but a large part is also devoted to practical usage of moments. Applications from various fields of computer vision, remote sensing, medical imaging, image retrieval, watermarking, and forensic analysis are demonstrated. Attention is also paid to efficient algorithms of moment computation. Key features: Presents a systematic overview of moment-based features used in 2D and 3D image analysis. Demonstrates invariant properties of moments with respect to various spatial and intensity transformations. Reviews and compares several orthogonal polynomials and respective moments. Describes efficient numerical algorithms for moment computation. It is a «classroom ready» textbook with a self-contained introduction to classifier design. The accompanying website contains around 300 lecture slides, Matlab codes, complete lists of the invariants, test images, and other supplementary material. 2D and 3D Image Analysis by Moments, is ideal for mathematicians, computer scientists, engineers, software developers, and Ph.D students involved in image analysis and recognition. Due to the addition of two introductory chapters on classifier design, the book may also serve as a self-contained textbook for graduate university courses on object recognition.

8108.19 рублей

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H. Huang K. PACS-Based Multimedia Imaging Informatics. Basic Principles and Applications

Thoroughly revised to present the very latest in PACS-based multimedia in medical imaging informatics—from the electronic patient record to the full range of topics in digital medical imaging—this new edition by the founder of PACS and multimedia image informatics features even more clinically applicable material than ever before. It uses the framework of PACS-based image informatics, not physics or engineering principles, to explain PACS-based multimedia informatics and its application in clinical settings and labs. New topics include Data Grid and Cloud Computing, IHE XDS-I Workflow Profile (Integrating the Healthcare Enterprise Cross-enterprise Document Sharing for Imaging), extending XDS to share images, and diagnostic reports and related information across a group of enterprise health care sites. PACS-Based Multimedia Imaging Informatics is presented in 4 sections. Part 1 covers the beginning and history of Medical Imaging, PACS, and Imaging Informatics. The other three sections cover Medical Imaging, Industrial Guidelines, Standards, and Compliance; Informatics, Data Grid, Workstation, Radiation Therapy, Simulators, Molecular Imaging, Archive Server, and Cloud Computing; and multimedia Imaging Informatics, Computer-Aided Diagnosis (CAD), Image-Guide Decision Support, Proton Therapy, Minimally Invasive Multimedia Image-Assisted Surgery, BIG DATA. New chapter on Molecular Imaging Informatics Expanded coverage of PACS and eHR's (Electronic Health Record), with HIPPA compliance New coverage of PACS-based CAD (Computer-Aided Diagnosis) Reorganized and expanded clinical chapters discuss one distinct clinical application each Minimally invasive image assisted surgery in translational medicine Authored by the world's first and still leading authority on PACS and medical imaging PACS-Based Multimedia Imaging Informatics: Basic Principles and Applications, 3rd Edition is the single most comprehensive and authoritative resource that thoroughly covers the critical issues of PACS-based hardware and software design and implementation in a systematic and easily comprehensible manner. It is a must-have book for all those involved in designing, implementing, and using PACS-based Multimedia Imaging Informatics.

18337.48 рублей

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Frank Shih Y. Image Processing and Pattern Recognition. Fundamentals and Techniques

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

12227.96 рублей

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Theo Gevers Color in Computer Vision. Fundamentals and Applications

While the field of computer vision drives many of today’s digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color in computer vision, this book provides a complete set of tools for working with color in the field of image understanding. Based on the authors’ intense collaboration for more than a decade and drawing on the latest thinking in the field of computer science, the book integrates topics from color science and computer vision, clearly linking theories, techniques, machine learning, and applications. The fundamental basics, sample applications, and downloadable versions of the software and data sets are also included. Clear, thorough, and practical, Color in Computer Vision explains: Computer vision, including color-driven algorithms and quantitative results of various state-of-the-art methods Color science topics such as color systems, color reflection mechanisms, color invariance, and color constancy Digital image processing, including edge detection, feature extraction, image segmentation, and image transformations Signal processing techniques for the development of both image processing and machine learning Robotics and artificial intelligence, including such topics as supervised learning and classifiers for object and scene categorization Researchers and professionals in computer science, computer vision, color science, electrical engineering, and signal processing will learn how to implement color in computer vision applications and gain insight into future developments in this dynamic and expanding field.

8884.05 рублей

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Frank Shih Y. Image Processing and Pattern Recognition. Fundamentals and Techniques

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

11651.72 рублей

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Arthur Goshtasby Ardeshir Theory and Applications of Image Registration

A hands-on guide to image registration theory and methods—with examples of a wide range of real-world applications Theory and Applications of Image Registration offers comprehensive coverage of feature-based image registration methods. It provides in-depth exploration of an array of fundamental issues, including image orientation detection, similarity measures, feature extraction methods, and elastic transformation functions. Also covered are robust parameter estimation, validation methods, multi-temporal and multi-modality image registration, methods for determining the orientation of an image, methods for identifying locally unique neighborhoods in an image, methods for detecting lines in an image, methods for finding corresponding points and corresponding lines in images, registration of video images to create panoramas, and much more. Theory and Applications of Image Registration provides readers with a practical guide to the theory and underpinning principles. Throughout the book numerous real-world examples are given, illustrating how image registration can be applied to problems in various fields, including biomedicine, remote sensing, and computer vision. Also provided are software routines to help readers develop their image registration skills. Many of the algorithms described in the book have been implemented, and the software packages are made available to the readers of the book on a companion website. In addition, the book: Explores the fundamentals of image registration and provides a comprehensive look at its multi-disciplinary applications Reviews real-world applications of image registration in the fields of biomedical imaging, remote sensing, computer vision, and more Discusses methods in the registration of long videos in target tracking and 3-D reconstruction Addresses key research topics and explores potential solutions to a number of open problems in image registration Includes a companion website featuring fully implemented algorithms and image registration software for hands-on learning Theory and Applications of Image Registration is a valuable resource for researchers and professionals working in industry and government agencies where image registration techniques are routinely employed. It is also an excellent supplementary text for graduate students in computer science, electrical engineering, software engineering, and medical physics.

10558.75 рублей

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A hands-on guide to image registration theory and methods—with examples of a wide range of real-world applications Theory and Applications of Image Registration offers comprehensive coverage of feature-based image registration methods. It provides in-depth exploration of an array of fundamental issues, including image orientation detection, similarity measures, feature extraction methods, and elastic transformation functions. Also covered are robust parameter estimation, validation methods, multi-temporal and multi-modality image registration, methods for determining the orientation of an image, methods for identifying locally unique neighborhoods in an image, methods for detecting lines in an image, methods for finding corresponding points and corresponding lines in images, registration of video images to create panoramas, and much more. Theory and Applications of Image Registration provides readers with a practical guide to the theory and underpinning principles. Throughout the book numerous real-world examples are given, illustrating how image registration can be applied to problems in various fields, including biomedicine, remote sensing, and computer vision. Also provided are software routines to help readers develop their image registration skills. Many of the algorithms described in the book have been implemented, and the software packages are made available to the readers of the book on a companion website. In addition, the book: Explores the fundamentals of image registration and provides a comprehensive look at its multi-disciplinary applications Reviews real-world applications of image registration in the fields of biomedical imaging, remote sensing, computer vision, and more Discusses methods in the registration of long videos in target tracking and 3-D reconstruction Addresses key research topics and explores potential solutions to a number of open problems in image registration Includes a companion website featuring fully implemented algorithms and image registration software for hands-on learning Theory and Applications of Image Registration is a valuable resource for researchers and professionals working in industry and government agencies where image registration techniques are routinely employed. It is also an excellent supplementary text for graduate students in computer science, electrical engineering, software engineering, and medical physics.

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